An estimated ten million people live with Parkinson's, yet timely diagnosis remains constrained by specialist assessment, costly imaging, and unequal care access. Phonation analysis offers a low-cost alternative: dopaminergic degeneration causes vocal impairments years before motor symptoms emerge, enabling community screening. However, existing ML approaches are limited by recording-level data leakage and opacity. This paper presents a four-phase acoustic framework-spanning signal acquisition, feature processing, and interpretable decision support-applied to a multi-type Parkinson's speech dataset (40 training, 28 blind-test). The framework enforces subject-level partitioning via GroupKFold... More >

Maternal mortality risk in Bangladesh remains a critical public health challenge, compounded by rural access gaps and the absence of scalable, data-driven early-warning systems. This study presents a reproducible, interpretable machine learning framework for maternal health risk classification using an IoT-collected dataset of 1,014 patient records and six physiological indicators; a deduplication audit identified 562 repeated sensor readings, a finding which is documented in the exploratory analysis. A rigorous pipeline was implemented encompassing five clinically grounded engineered features - Mean Arterial Pressure, Shock Index, Pulse Pressure, BP Ratio, and Composite Risk Score - alongsi... More >

Maternal mortality in Bangladesh remains a critical public health challenge, with recent evidence indicating stagnation in mortality reduction despite expanded facility-based delivery and skilled birth attendance. Accurate identification of high-risk cases is essential to enable targeted intervention and resource allocation. This study develops an interpretable machine learning framework for maternal mortality prediction using the nationally representative Bangladesh Maternal Mortality Survey 2016 (BMMS-2016). A comprehensive data integration and feature engineering pipeline was implemented across demographic, socioeconomic, and maternal healthcare domains. Given the severe class imbalance i... More >